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In this paper we present a neurally plausible model of robot reachinginspired by human infant reaching that is based on embodied artificialintelligence, which emphasizes the importance of the sensory-motor interactionof an agent and the world. This model encompasses both learning sensory-motorcorrelations through motor babbling and also arm motion planning usingspreading activation. This model is organized in three layers of neural mapswith parallel structures representing the same sensory-motor space. The motorbabbling period shapes the structure of the three neural maps as well as theconnections within and between them. We describe an implementation of thismodel and an investigation of this implementation using a simple reaching taskon a humanoid robot. The robot has learned successfully to plan reachingmotions from a test set with high accuracy and smoothness.

Neurally Plausible Model of Robot Reaching Inspired by Infant Motor Babbling